AbstractIn Italy, approximately 400.000 new cases of malignant tumors are recorded every year. The average of annual deaths caused by tumors, according to the Italian Cancer Registers, is about 3.5 deaths and about 2.5 per 1,000 men and women respectively, for a total of about 3 deaths every 1,000 people. Long-term (at least a decade) and spatially detailed data (up to the municipality scale) are neither easily accessible nor fully available for public consultation by the citizens, scientists, research groups, and associations. Therefore, here we present a ten-year (2009–2018) database on cancer mortality rates (in the form of Standardized Mortality Ratios, SMR) for 23 cancer macro-types in Italy on municipal, provincial, and regional scales. We aim to make easily accessible a comprehensive, ready-to-use, and openly accessible source of data on the most updated status of cancer mortality in Italy for local and national stakeholders, researchers, and policymakers and to provide researchers with ready-to-use data to perform specific studies. Methods For a given locality, year, and cause of death, the SMR is the ratio between the observed number of deaths (Om) and the number of expected deaths (Em): SMR = Om/Em (1) where Om should be an available observational data and Em is estimated as the weighted sum of age-specific population size for the given locality (ni) per age-specific death rates of the reference population (MRi): Em = sum(MRi x ni) (2) MRi could be provided by a public health organization or be estimated as the ratio between the age-specific number of deaths of reference population (Mi) to the age-specific reference population size (Ni): MRi = Mi/Ni (3) Thus, the value of Em is weighted by the age distribution of deaths and population size. SMR assumes value 1 when the number of observed and expected deaths are equal. Following eqns. (1-3), the SMR was computed for single years of the period 2009-2018 and for single cause of death as defined by the International ICD-10 classification system by using the following data: age-specific number of deaths by cause of reference population (i.e., Mi) from the Italian National Institute of Statistics (ISTAT, (http://www.istat.it/en/, last access: 26/01/2022)); age-specific census data on reference population (i.e., Ni) from ISTAT; the observed number of deaths by cause (i.e., Om) from ISTAT; the age-specific census data on population (ni); the SMR was estimated at three different level of aggregation: municipal, provincial (equivalent to the European classification NUTS 3) and regional (i.e., NUTS2). The SMR was also computed for the broad category of malignant tumors (i.e. C00-C979, hereinafter cancer macro-type C), and for the broad category of malignant tumor plus non-malignant tumors (i.e. C00-C979 plus D0-D489, hereinafter cancer macro-type CD). Lower 90% and 95% confidence intervals of 10-year average values were computed according to the Byar method.

Number and rate of new cancer cases diagnosed annually from 1992 to the most recent diagnosis year available. Included are all invasive cancers and in situ bladder cancer with cases defined using the Surveillance, Epidemiology and End Results (SEER) Groups for Primary Site based on the World Health Organization International Classification of Diseases for Oncology, Third Edition (ICD-O-3). Random rounding of case counts to the nearest multiple of 5 is used to prevent inappropriate disclosure of health-related information.

This dataset, released February 2021, contains the statistics of premature mortality by various causes for people below 75 years, over the years 2014 to 2018. Causes for death include cancer (colorectal, lung, breast), diabetes, circulatory system diseases (ischaemic heart disease, cerebrovascular disease), respiratory system diseases (chronic obstructive pulmonary disease), and external causes (road traffic injuries, suicide and self-inflicted injuries) The data is by Local Government Area (LGA) 2016 geographic boundaries. For more information please see the data source notes on the data. Source: Data compiled by PHIDU from deaths data based on the 2014 to 2018 Cause of Death Unit Record Files supplied by the Australian Coordinating Registry and the Victorian Department of Justice, on behalf of the Registries of Births, Deaths and Marriages and the National Coronial Information System. The population is the ABS Estimated Resident Population (ERP) for Australia, 30 June 2014 to 30 June 2018. AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

BackgroundCervical cancer incidence and mortality rates in the United States have substantially declined over recent decades, primarily driven by reductions in squamous cell carcinoma cases. However, the trend in recent years remains unclear. This study aimed to explore the trends in cervical cancer incidence and mortality, stratified by demographic and tumor characteristics from 1975 to 2018.MethodsThe age-adjusted incidence, incidence-based mortality, and relative survival of cervical cancer were calculated using the Surveillance, Epidemiology, and End Results (SEER)-9 database. Trend analyses with annual percent change (APC) and average annual percent change (AAPC) calculations were performed using Joinpoint Regression Software (Version 4.9.1.0, National Cancer Institute).ResultsDuring 1975–2018, 49,658 cervical cancer cases were diagnosed, with 17,099 recorded deaths occurring between 1995 and 2018. Squamous cell carcinoma was the most common histological type, with 34,169 cases and 11,859 deaths. Over the study period, the cervical cancer incidence rate decreased by an average of 1.9% (95% CI: −2.3% to −1.6%) per year, with the APCs decreased in recent years (−0.5% [95% CI: −1.1 to 0.1%] in 2006–2018). Squamous cell carcinoma incidence trends closely paralleled overall cervical cancer patterns, but the incidence of squamous cell carcinoma in the distant stage increased significantly (1.1% [95% CI: 0.4 to 1.8%] in 1990–2018). From 1995 to 2018, the overall cervical cancer mortality rate decreased by 1.0% (95% CI: −1.2% to −0.8%) per year. But for distant-stage squamous cell carcinoma, the mortality rate increased by 1.2% (95% CI: 0.3 to 2.1%) per year.ConclusionFor cervical cancer cases diagnosed in the United States from 1975 to 2018, the overall incidence and mortality rates decreased significantly. However, there was an increase in the incidence and mortality of advanced-stage squamous cell carcinoma. These epidemiological patterns offer critical insights for refining cervical cancer screening protocols and developing targeted interventions for advanced-stage cases.

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

The role of religion and politics in the responses to the coronavirus pandemic raises the question of their influence on the risk of other diseases. This study focuses on age-adjusted death rates of cancer, heart disease, and infant mortality per 1000 live births before the pandemic (2018-2019) and COVID-19 in 2020-2021. Eight hypothesized predictors of health effects were analyzed by examining their correlation to age-adjusted death rates among U.S. states, percentage who pray once or more daily, Republican influence on state health policies as indicated by the percentage vote for Trump in 2016, percent of household incomes below poverty, median family income divided by a cost-of-living index, the Gini income inequality index, urban concentration of the population, physicians per capita, and public health expenditures per capita. Since prayer for divine intervention is common to otherwise diverse religious beliefs and practices, the percentage of people claiming to pray daily in each state was used to indicate potential religious influence. All of the death rates were higher in states where more people claimed to pray daily, and where Trump received a larger percentage of the vote. Except for COVID-19, the death rates were consistently lower in states with higher public health expenditures per capita. Only COVID-19 was correlated to physicians per capita, lower where there were more physicians. Corrected statistically for the other factors, income per cost of living explains no variance. Heart disease and COVID-19 death rates were higher in areas with more income inequality. All of the disease rates were in correlation with more rural populations. Correlation of daily prayer with smoking cigarettes, and neglect of public health recommendations for fruit and vegetable consumption and COVID-19 vaccination suggests that prayer may be substituted for preventive practices.

This table contains 4032 series, with data for years 1994/1998 - 2009/2013 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (6 items: Canada; Inuit Nunangat; Inuvialuit Region; Nunavut; ...) Sex (3 items: Both sexes; Males; Females) Indicators (2 items: Mortality; Potential years of life lost) Selected causes of death (16 items: Total, all causes of death; All malignant neoplasms (cancers); Colorectal cancer; Lung cancer; ...) Characteristics (7 items: Number; Rate; Low 95% confidence interval, rate; High 95% confidence interval, rate; ...).

These data come from a series of surveys that all relate to understanding the difficulties people have in talking to each other. We investigated: - what concerns/fears people have about talking to strangers and having difficult conversations with acquaintances (e.g., about miscarriage, bereavement, a cancer diagnosis) and close others (e.g., about death and dying) - how these concerns are similar/different across these contexts (e.g., do people worry about similar things when they consider talking to a stranger vs. talking to an acquaintance about bereavement)Humans are social beings who need to feel connected to people, and understood by others in order to thrive. When this need to belong is not met, there are serious negative consequences for physical and mental health. Indeed, loneliness puts people at as much risk of early death as smoking, and at greater risk than obesity (Holt-Lunstad, Smith & Layton, 2010). Loneliness is a widespread social issue in the UK; a recent poll conducted by the Jo Cox commission on loneliness found that "almost three-quarters of older people in the UK are lonely" (The Guardian, 2017). Given the prevalence of loneliness, and its negative consequences, it is crucial to understand the intrapersonal and situational barriers that discourage people from talking to one another, and thus constrain people from fulfilling their need to belong. An understanding of these barriers will form the basis of interventions to encourage more frequent - and more positive - interactions. People generally enjoy socializing and spend a great deal of time talking, but in certain situations they struggle to know what words to say. For example, most people find it challenging to talk to someone who is experiencing a difficult situation (e.g., a cancer diagnosis, the loss of a loved one). It is said that in times of trouble, you find out who your real friends are; the people who let you down decide they're better off to say nothing at all rather than say the "wrong" thing. What exactly are people worried about, and are there actually "wrong" things to say? This project will address these questions, and draw upon the answers to identify ways of increasing the frequency and quality of interactions, thus improving the social support people receive when they need it most. My recent research has focused on talking to strangers - another situation that finds many people at a loss for words. I have found that, although talking to strangers is generally enjoyable and makes people feel connected, people report a wide range of worries about doing it. The proposed project will build upon this work by examining not only how people feel before social interactions, but also what they say during interactions. Importantly, this project will go beyond the single situation of talking to a stranger, to test the extent to which these predictors of interaction success (i.e., how people feel and what they say) are similar across situations (e.g., talking to a person of a different ethnicity, a wheelchair user, a cancer patient). Evidence of similarities across people and situations will prove invaluable in developing interventions to improve interaction success. This project will begin by collecting descriptive information about 1) the worries people have when considering different types of social interactions ("fears"; e.g., their partner might not talk enough, or might not like them), and 2) the things people wish that others would and would not say ("phrases"; e.g., both cancer patients and people living with disability dislike it when people tell them they're "so brave"). Next, I will extract themes from these qualitative responses, and develop survey instruments to assess fears and phrase use. This will allow me to quantitatively examine the extent to which fears and phrase use vary between people (i.e., related to individual differences) and within people (i.e., related to the situation). Then I will run experiments to examine the effects of fears and phrases on interaction success in real-life social interactions, ultimately testing interventions with the goal of increasing interaction success. The research findings will be of interest to health care professionals, and a range of social organisations that work to fight loneliness, to encourage social acceptance and integration (e.g., for the disabled, for minority ethnic people), or to support people confronting difficult situations (e.g., bereavement, serious illness). Data was compiled through a sequence of online surveys, each designed to explore the challenges individuals face in engaging in conversations with others.

PurposeBone is one of the most common sites for the spread of malignant tumors. Patients with bone metastases whose prognosis was shorter than 3 months (early death) were considered as surgical contraindications. However, the information currently available in the literature limits our capacity to assess the risk likelihood of 3 month mortality. As a result, the study's objective is to create an accurate prediction model utilizing machine-learning techniques to predict 3 month mortality specifically among lung cancer patients with bone metastases according to easily available clinical data.MethodsThis study enrolled 19,887 lung cancer patients with bone metastases between 2010 and 2018 from a large oncologic database in the United States. According to a ratio of 8:2, the entire patient cohort was randomly assigned to a training (n = 15881, 80%) and validation (n = 4,006, 20%) group. In the training group, prediction models were trained and optimized using six approaches, including logistic regression, XGBoosting machine, random forest, neural network, gradient boosting machine, and decision tree. There were 13 metrics, including the Brier score, calibration slope, intercept-in-large, area under the curve (AUC), and sensitivity, used to assess the model's prediction performance in the validation group. In each metric, the best prediction effectiveness was assigned six points, while the worst was given one point. The model with the highest sum score of the 13 measures was optimal. The model's explainability was performed using the local interpretable model-agnostic explanation (LIME) according to the optimal model. Predictor importance was assessed using H2O automatic machine learning. Risk stratification was also evaluated based on the optimal threshold.ResultsAmong all recruited patients, the 3 month mortality was 48.5%. Twelve variables, including age, primary site, histology, race, sex, tumor (T) stage, node (N) stage, brain metastasis, liver metastasis, cancer-directed surgery, radiation, and chemotherapy, were significantly associated with 3 month mortality based on multivariate analysis, and these variables were included for developing prediction models. With the highest sum score of all the measurements, the gradient boosting machine approach outperformed all the other models (62 points), followed by the XGBooting machine approach (59 points) and logistic regression (53). The area under the curve (AUC) was 0.820 (95% confident interval [CI]: 0.807–0.833), 0.820 (95% CI: 0.807–0.833), and 0.815 (95% CI: 0.801–0.828), respectively, calibration slope was 0.97, 0.95, and 0.96, respectively, and accuracy was all 0.772. Explainability of models was conducted to rank the predictors and visualize their contributions to an individual's mortality outcome. The top four important predictors in the population according to H2O automatic machine learning were chemotherapy, followed by liver metastasis, radiation, and brain metastasis. Compared to patients in the low-risk group, patients in the high-risk group were more than three times the odds of dying within 3 months (P < 0.001).ConclusionsUsing machine learning techniques, this study offers a number of models, and the optimal model is found after thoroughly assessing and contrasting the prediction performance of each model. The optimal model can be a pragmatic risk prediction tool and is capable of identifying lung cancer patients with bone metastases who are at high risk for 3 month mortality, informing risk counseling, and aiding clinical treatment decision-making. It is better advised for patients in the high-risk group to have radiotherapy alone, the best supportive care, or minimally invasive procedures like cementoplasty.

ObjectiveThe role of spousal support has been recognized to benefit patients with many chronic diseases and cancers. However, the impact of marital status on the survival of middle-aged and elderly patients with primary bone tumors remains elusive.Materials and methodsThe data of patients aged ≥ 45 years with primary bone tumors diagnosed between 2000 and 2018 were extracted from the Surveillance, Epidemiology, and End Results Database. Kaplan–Meier analysis was used to assess the overall survival and tumor-specific survival of patients. The Cox proportional hazards and Fine-and-Gray models were used to calculate the hazard ratios (HRs) and sub-distribution HRs (sHR) and the corresponding 95% confidence interval (CI) of all-cause mortality and tumor-specific mortality, respectively.ResultsA total of 5,640 primary bone tumors were included in the study. In 45–59 years cohort, married, unmarried, divorced and widowed accounted for 66.0, 21.0, 11.2, and 1.8%, respectively; while 64.3, 10.1, 8.8, and 16.8% in 60+ years cohort, respectively. The widowed patients had a lower proportion of early-stage tumors at diagnosis than that married, unmarried, and divorced patients (31.0% vs. 36% vs. 37.1% vs. 39.4%; P = 0.008), and had a higher proportion of patients who did not undergo surgery than that of married, unmarried, and divorced patients (38.6% vs. 21.3% vs. 24.6% vs. 24.4%; P < 0.001). The widowed population had an increased risk of all-cause mortality (HR, 1.68; 95% CI, 1.50–1.88; P < 0.001) and disease-related mortality (HR, 1.33; 95% CI, 1.09–1.61; P = 0.005) compared with the married population.ConclusionThe marital status of middle-aged and elderly people can affect the tumor stage at diagnosis, treatment, and survival prognosis of patients with primary bone cancer. Widowed patients are more inclined to choose non-surgical treatment and have the worst prognosis.

IntroductionIn patients with Common Variable Immunodeficiency, malignancy has been reported as the leading cause of death in adults, with a high risk of B-cell lymphomas and gastric cancer.MethodsWe conducted a five-year prospective study aiming to update the incidence and mortality of gastric cancer and the incidence of gastric precancerous lesions in 512 CVID patients who underwent a total of 400 upper gastrointestinal endoscopies.ResultsIn the pre-pandemic period, 0.58 endoscopies were performed per patient/year and in the COVID-19 period, 0.39 endoscopies were performed per patient/year. Histology revealed areas with precancerous lesions in about a third of patients. Patients who had more than one gastroscopy during the study period were more likely to have precancerous lesions. Two patients received a diagnosis of gastric cancer in the absence of Helicobacter pylori infection. The overall prevalence of Helicobacter pylori infection in biopsy specimens was 19.8% and related only to active gastritis. Among patients who had repeated gastroscopies, about 20% progressed to precancerous lesions, mostly independent of Helicobacter pylori.DiscussionWhile gastric cancer accounted for one in five deaths from CVID in our previous survey, no gastric cancer deaths were recorded in the past five years, likely consistent with the decline in stomach cancer mortality observed in the general population. However, during the COVID-19 pandemic, cancer screening has been delayed. Whether such a delay or true decline could be the reason for the lack of gastric cancer detection seen in CVID may become clear in the coming years. Due to the high incidence of precancerous lesions, we cannot rely on observed and predicted trends in gastric cancer mortality and strongly recommend tailored surveillance programs.

Poorer survival in cancer patients with vs. without comorbidity has been reported for various cancer sites. For patients with colorectal cancer (CRC), limited data are available so far. Patients with CRC diagnosed between 2010 and 2018 were identified in a health claims database covering 20% of the German population. We assessed the prevalence of comorbidities at cancer diagnosis and categorized the patients into the groups: ‘none’, ‘somatic only’, ‘mental only’ or ‘both’ types of comorbidities. Hazard ratios (HR, with 95% confidence intervals) for five-year overall survival were estimated by Cox proportional hazard models, adjusted for age, sex and stage at diagnosis (advanced vs. non-advanced). We included 92,991 patients (females: 49.1%, median age: 72 years) with a median follow-up of 30 months. The proportions assigned to the groups ‘none’, ‘somatic only’, ‘mental only’ or ‘both’ were 24.7%, 65.5%, 1.4% and 8.4%. Overall, 32.8% of the patients died during follow-up. Compared to patients without comorbidities (‘none’), the adjusted HR regarding death from any cause was 1.11 (95% CI: 1.07–1.14) in the group ‘somatic only’, 1.74 (95% CI: 1.58–1.92) in the group ‘mental only’ and 1.92 (95% CI: 1.84–2.00) in the group ‘both’. For patients with ‘mental only’ comorbidities, the adjusted HR was higher in males than in females (HR = 2.19, 95% CI: 1.88–2.55 vs. HR = 1.55, 95% CI: 1.37–1.75). Our results suggest that patients with CRC and with mental comorbidities, particularly males, have a markedly lower overall survival compared to those without any or only somatic comorbidities.

Breast cancer is one of the most frequent cancer types worldwide and the first cause of cancer-related deaths in women. Although significant therapeutic advances have been achieved with drugs such as tamoxifen and trastuzumab, breast cancer still caused 627,000 deaths in 2018. Since cancer is a multifactorial disease, it has become necessary to develop new molecular therapies that can target several relevant cellular processes at once. Ion channels are versatile regulators of several physiological- and pathophysiological-related mechanisms, including cancer-relevant processes such as tumor progression, apoptosis inhibition, proliferation, migration, invasion, and chemoresistance. Ion channels are the main regulators of cellular functions, conducting ions selectively through a pore-forming structure located in the plasma membrane, protein–protein interactions one of their main regulatory mechanisms. Among the different ion channel families, the Transient Receptor Potential (TRP) family stands out in the context of breast cancer since several members have been proposed as prognostic markers in this pathology. However, only a few approaches exist to block their specific activity during tumoral progress. In this article, we describe several TRP channels that have been involved in breast cancer progress with a particular focus on their binding partners that have also been described as drivers of breast cancer progression. Here, we propose disrupting these interactions as attractive and potential new therapeutic targets for treating this neoplastic disease.

BackgroundHepatitis C virus (HCV) infection affects men and women differently, yet few studies have investigated sex differences in long-term mortality risk among the HCV-infected population. We conducted a population-based study to elucidate all-cause and cause-specific mortality among men and women with HCV infection.MethodsThe study population consisted of adult participants from the 1999–2018 National Health and Nutrition Examination Survey, including 945 HCV-infected and 44,637 non-HCV-infected individuals. HCV infection was defined as either HCV seropositivity or detectable HCV RNA. Participants were followed until the date of death or December 31, 2019, to determine survival status.ResultsThe HCV-infected population, both male and female, tended to be older, more likely to be Black, single, have lower income, lower BMI, higher prevalence of hypertension, and were more likely to be current smokers. During a median follow-up of 125.0 months, a total of 5,309 participants died, including 1,253 deaths from cardiovascular disease (CVD) and 1,319 deaths from cancer. The crude analysis showed that the risk of death from all causes and from cancer, but not from CVD, was higher in the HCV-infected population. After adjusting for potential confounders, we found that both HCV-infected men (HR 1.41, 95% CI 1.10–1.81) and women (HR 2.03, 95% CI 1.36–3.02) were equally at increased risk of all-cause mortality compared to their non-HCV infected counterparts (p for interaction > 0.05). The risk of cancer-related mortality was significantly increased in HCV-infected women (HR 2.14, 95% CI 1.01–4.53), but not in men, compared to non-HCV-infected counterparts. Among HCV-infected population, there was no difference in the risks of all-cause, CVD-related, or cancer-related death between men and women.ConclusionBoth men and women with HCV infection had an increased risk of death from all causes compared to their non-HCV infected counterparts, but we did not observe a significant sex difference.

Risk of death from all causes, cardiovascular disease (CVD), and cancer in men compared to women (reference group), both for the total population and stratified by hepatitis C virus (HCV) infection status.